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OrcaSong: Preprocessing KM3NeT data for DL

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The documentation for OrcaSong can be found at https://ml.pages.km3net.de/OrcaSong!

OrcaSong is a part of the Deep Learning efforts of the neutrino telescope KM3NeT. Find more information about KM3NeT on http://www.km3net.org.

In this regard, OrcaSong is a project that preprocesses raw KM3NeT detector data for the use with deep neural networks, making use of km3nets data processing pipline km3pipe. Two different modes are available:

  • For convolutional networks: produce n-dimensional 'images' (histograms)
  • For graph networks: produce a list of nodes, each node representing infos about a hit in the detector

Currently, only simulations with a hdf5 data format are supported as an input.

OrcaSong can be installed via pip by running:

pip install orcasong

You can get a list of all the bash commands in orcasong by typing:

orcasong --help

Containerization

The easiest way to run OrcaSong is with singularity. A Singularity image of the latest stable version of OrcaSong is automatically uploaded to our sftp server. Download it e.g. via:

wget http://pi1139.physik.uni-erlangen.de/singularity/orcasong_v???.sif

where v??? is the version, e.g. orcasong_v4.3.2.sif. Run it e.g. via:

singularity shell orcasong_v???.sif

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